Chaos synchronization of coupled neurons under electrical stimulation via robust adaptive fuzzy control

Yan Qiu Che, Jiang Wang, Wai Lok Chan, Kai Ming Tsang

Research output: Contribution to journalArticle

24 Scopus citations

Abstract

This paper presents a robust adaptive fuzzy controller to synchronize two gap junction coupled chaotic FitzHugh-Nagumo (FHN) neurons under external electrical stimulation. A variable universe adaptive fuzzy approximator is used to approximate the nonlinear uncertain function of the synchronization error system. Based on the Lyapunov stability theory, the obtained adaptive laws of fuzzy algorithm not only guarantee the stability of the closed loop error system, but also attenuate the influence of matching error and external disturbance on synchronization error to an arbitrarily desired level. Chaos synchronization is obtained by proper choice of the control parameters. The simulation results demonstrate the effectiveness of the proposed control method.

Original languageEnglish (US)
Pages (from-to)847-857
Number of pages11
JournalNonlinear Dynamics
Volume61
Issue number4
DOIs
Publication statusPublished - Sep 1 2010

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All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Aerospace Engineering
  • Ocean Engineering
  • Mechanical Engineering
  • Applied Mathematics
  • Electrical and Electronic Engineering

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